Generative AI for Performance ReportingArtificial Intelligence (AI)

In any city around the world 00447455203759 Course Code: d

Course Description

Introduction

Generative AI can help performance teams produce faster, clearer, and more consistent performance reports by drafting narratives, summarizing results, and highlighting key insights. This practical program equips Grade 5 performance specialists with simple, safe workflows to use generative AI for reporting—while maintaining accuracy, confidentiality, and strong human review.

Course Objectives

By the end of this course, participants will be able to:

·        Use GenAI to draft performance report narratives

·        Standardize reporting language and formats

·        Summarize KPI results and key changes

·        Apply quality checks to prevent errors

·        Follow safe-use rules for sensitive data

Target Audience

This course is designed for:

·        Senior Specialist  performance management staff

·        KPI and reporting coordinators

·        Performance dashboards and reporting teams

·        Quality and controls staff supporting reports

·        Teams preparing executive performance packs

Course Outlines

Day 1: GenAI Basics for Reporting

·        Where GenAI helps in reporting

·        Limitations and risks

·        Prompting basics for narratives

·        Safe use and confidentiality

·        Activity: Build a reporting prompt set

Day 2: KPI Narratives and Commentary

·        Writing clear KPI commentary

·        Explaining changes and trends

·        Variance and driver wording basics

·        Recommendations and next steps

·        Workshop: Draft KPI commentary with AI

Day 3: Building Performance Report Packs

·        Report structure and sections

·        Executive summary drafting

·        Highlights, risks, and actions

·        Action log and owners

·        Activity: Create a full report pack

Day 4: Quality Control and Verification

·        Fact checking numbers and dates

·        Preventing hallucinations

·        Consistency across sections

·        Version control and approvals

·        Case study: Fix AI reporting errors 

Day 5: Adoption and Continuous Improvement

·        Workflow and review gates

·        Prompt library and templates

·        Metrics: cycle time and errors

·        90-day adoption plan

·        Final project: GenAI reporting playbook